{"id":"https://openalex.org/W2999563477","doi":"https://doi.org/10.1109/access.2020.2964760","title":"Classification of Very High-Resolution Remote Sensing Imagery Using a Fully Convolutional Network With Global and Local Context Information Enhancements","display_name":"Classification of Very High-Resolution Remote Sensing Imagery Using a Fully Convolutional Network With Global and Local Context Information Enhancements","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2999563477","doi":"https://doi.org/10.1109/access.2020.2964760","mag":"2999563477"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2964760","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2964760","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2020.2964760","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047532495","display_name":"Huanjun Hu","orcid":"https://orcid.org/0000-0003-1738-5165"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huanjun Hu","raw_affiliation_strings":["School of Resource and Environment Sciences, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-1738-5165","affiliations":[{"raw_affiliation_string":"School of Resource and Environment Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101638605","display_name":"Zheng Li","orcid":"https://orcid.org/0000-0002-3358-9478"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Li","raw_affiliation_strings":["Hubei Institute of Land Surveying and Mapping, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei Institute of Land Surveying and Mapping, Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412846","display_name":"Lin Li","orcid":"https://orcid.org/0000-0002-2034-982X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":["RE-Institute of Smart Perception and Intelligent Computing, Wuhan University, Wuhan, China","School of Resource and Environment Sciences, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RE-Institute of Smart Perception and Intelligent Computing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Resource and Environment Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101436329","display_name":"Hui Yang","orcid":"https://orcid.org/0000-0002-6701-6766"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]},{"id":"https://openalex.org/I2802624667","display_name":"Hefei Institutes of Physical Science","ror":"https://ror.org/046n57345","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Yang","raw_affiliation_strings":["Institutes of Physical Science and Information Technology, Anhui University, Hefei, China","School of Resource and Environment Sciences, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institutes of Physical Science and Information Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I2802624667","https://openalex.org/I143868143"]},{"raw_affiliation_string":"School of Resource and Environment Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101920570","display_name":"Haihong Zhu","orcid":"https://orcid.org/0000-0003-2503-0700"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haihong Zhu","raw_affiliation_strings":["School of Resource and Environment Sciences, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Resource and Environment Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5047532495"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.7212,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.87927735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"14606","last_page":"14619"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7993993759155273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.700897216796875},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6606925129890442},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5738120079040527},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.537071943283081},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5364084839820862},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5112121105194092},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41968441009521484},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40874338150024414},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3273482322692871},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07388827204704285}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7993993759155273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.700897216796875},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6606925129890442},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5738120079040527},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.537071943283081},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5364084839820862},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5112121105194092},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41968441009521484},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40874338150024414},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3273482322692871},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07388827204704285},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2964760","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2964760","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:03a4993c633f4816a0c2292b86180c84","is_oa":true,"landing_page_url":"https://doaj.org/article/03a4993c633f4816a0c2292b86180c84","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 14606-14619 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2964760","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2964760","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4399999976158142,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2944953391","display_name":null,"funder_award_id":"41571395","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6081697977","display_name":null,"funder_award_id":"2016YFB0501403","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6648801017","display_name":null,"funder_award_id":"41971311","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7120072391","display_name":null,"funder_award_id":"41471328","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8058653261","display_name":null,"funder_award_id":"41871298","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8649209071","display_name":null,"funder_award_id":"41271443","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327063","display_name":"National Administration of Surveying, Mapping and Geoinformation of China","ror":"https://ror.org/04z3map19"},{"id":"https://openalex.org/F4320334897","display_name":"Natural Science Foundation of Anhui Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1899185266","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1963860205","https://openalex.org/W1973944664","https://openalex.org/W1993056320","https://openalex.org/W2022686119","https://openalex.org/W2028546171","https://openalex.org/W2066916495","https://openalex.org/W2067709907","https://openalex.org/W2079745808","https://openalex.org/W2090273608","https://openalex.org/W2095819230","https://openalex.org/W2106587382","https://openalex.org/W2115451191","https://openalex.org/W2124537004","https://openalex.org/W2127199143","https://openalex.org/W2143354507","https://openalex.org/W2144764737","https://openalex.org/W2152414269","https://openalex.org/W2152640741","https://openalex.org/W2253590344","https://openalex.org/W2294774991","https://openalex.org/W2341130385","https://openalex.org/W2344884875","https://openalex.org/W2408060227","https://openalex.org/W2412588858","https://openalex.org/W2480078828","https://openalex.org/W2488187315","https://openalex.org/W2527276685","https://openalex.org/W2550553598","https://openalex.org/W2559597482","https://openalex.org/W2595745675","https://openalex.org/W2610528085","https://openalex.org/W2616755213","https://openalex.org/W2752782242","https://openalex.org/W2787614951","https://openalex.org/W2890732922","https://openalex.org/W2897283027","https://openalex.org/W2900094710","https://openalex.org/W2901117552","https://openalex.org/W2901958353","https://openalex.org/W2951841689","https://openalex.org/W2963446712","https://openalex.org/W2963495494","https://openalex.org/W2963659230","https://openalex.org/W2963881378","https://openalex.org/W2963977677","https://openalex.org/W2963995737","https://openalex.org/W2964309882","https://openalex.org/W2997225633","https://openalex.org/W4253153980","https://openalex.org/W6639927594","https://openalex.org/W6640295612","https://openalex.org/W6713905957","https://openalex.org/W6722710385","https://openalex.org/W6727577265","https://openalex.org/W6748481559","https://openalex.org/W6751733626"],"related_works":["https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W2969228573","https://openalex.org/W2963690996","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"methods":[2,21],"for":[3,68,88,99],"semantic":[4,70,107],"image":[5],"segmentation":[6,71,108,188],"can":[7,186],"effectively":[8],"extract":[9],"geographical":[10,43],"features":[11,26],"from":[12],"very":[13],"high-resolution":[14],"(VHR)":[15],"remote":[16,74],"sensing":[17,75],"images.":[18,76],"However,":[19],"these":[20],"experience":[22],"over-segmentation":[23],"in":[24,30,121,183],"low-level":[25],"and":[27,54,91,129,139,147,155,163,165,171,189],"a":[28,48,64,81,92],"breakdown":[29],"the":[31,41,69,78,105,122,137,142,149,157,166,178,194],"integrity":[32,192],"of":[33,72,110],"objects":[34],"with":[35,136],"fixed":[36],"patch":[37],"sizes":[38],"due":[39],"to":[40,62],"multi-scaled":[42],"features.":[44],"In":[45,77],"this":[46,184],"study,":[47],"dual":[49,179],"attention":[50,83,94,180],"mechanism":[51,181],"is":[52,86,97],"introduced":[53],"embedded":[55],"into":[56],"densely":[57],"connected":[58],"convolutional":[59],"networks":[60],"(DenseNets)":[61],"form":[63],"dense-global-entropy":[65],"network":[66,103],"(DGEN)":[67],"VHR":[73],"DGEN":[79],"architecture,":[80],"global":[82],"enhancement":[84],"module":[85,96],"developed":[87],"context":[89],"acquisition,":[90],"local":[93],"fusion":[95],"designed":[98],"detail":[100],"selection.":[101],"This":[102],"presents":[104],"improved":[106],"performance":[109],"test":[111],"ISPRS":[112],"2D":[113],"datasets.":[114],"The":[115,174],"experimental":[116],"results":[117],"indicate":[118],"an":[119],"improvement":[120],"overall":[123],"accuracy":[124],"(OA),":[125],"F1,":[126],"kappa":[127,158],"coefficient":[128,159],"mean":[130,150],"intersection":[131],"over":[132],"union":[133],"(MIoU).":[134],"Compared":[135],"DeeplabV3+":[138],"SegNet":[140],"models,":[141],"OA":[143],"improves":[144,152,160,168],"by":[145,153,161,169],"2.79%":[146],"1.19%;":[148],"F1":[151],"3.43%":[154],"0.88%;":[156],"4.04%":[162],"1.82%;":[164],"MIoU":[167],"5.22%":[170],"1.47%,":[172],"respectively.":[173],"experiments":[175],"showed":[176],"that":[177],"presented":[182],"study":[185],"improve":[187],"maintain":[190],"object":[191],"during":[193],"encoding-decoding":[195],"process.":[196]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}